Teach with expert insights on AI, curated by your trusty Teacher’s AIde

Welcome back to Teacher's AIed, where we generalize AI topics far more accurately than the "i before e except after c" rule. “The weird sovereign decided to seize the opportunity for a leisurely stroll, sipping on caffeine while admiring the beige veil of the evening sky, contemplating the height and weight of his decisions, neither forfeiting nor counterfeiting his protein-rich diet” (thank you ChatGPT).

Story-Time: My mom asked me to weigh in on the recent news reports on Google’s Gemini Image Creator.

In case you missed it here’s a brief summary: “when asked for an image of a Founding Father of America, Gemini showed a Black man, a Native American man, an Asian man, and a relatively dark-skinned man. Asked for a portrait of a pope, it showed a Black man and a woman of color. Nazis, too, were reportedly portrayed as racially diverse” (Vox).

Of course, there are political and cultural themes to this. These, I will avoid.

However, what I want to take a deeper-dive in to are the AI literacy components and their implications in K-12 Education.

Why is it that a generative-AI tool’s can be biased?

Without getting into the technical nitty-gritty, how do AI tools work?

How do AI tools sense the world and make judgements based on those sensations?

What does it mean to say that computers can “learn?”

How is it that AI-encoded computers can mimic organic, human capabilities?

This post is the first in a six part series on the AI4K12 Big Ideas in AI Framework. In each of the 5 biweekly posts that follow, I’ll dive into another one of their “Big Ideas” surrounding AI literacy.

What is AI Literacy? Keep reading to find out.

1. What is AI Literacy?

To ground a simple answer in the earlier example, one component of AI Literacy is knowing that an AI-created image will not necessarily be historically accurate. AI-generators are not search engines.

(I even went as far to lay out an analogy when chatting with my mom: asking generative-AI for a historically accurate image is like asking a microwave to make crunchy, perfectly toasted bread. It’s just the wrong machine for the job.)

This is just one small, niche example in the much larger domain of AI Literacy.

“Long & Magerko (2020) summarize it [AI Literacy] as a set of competencies that enables individuals to critically evaluate AI technologies; communicate and collaborate effectively with AI; and use AI as a tool online, at home, and in the workplace.” (Babson College).

Babson College further categorized AI Literacy according to 3 competencies:

Simply put, to be AI Literate requires some degree of knowledge how AI works, the ability to evaluate which AI tools are appropriate for a job, and the understanding of potential ethical implications of AI.

Why is this important for students?

2. Why is AI Literacy So Important?

One answer? Jobs.

For a while, the common refrain around AI and jobs was that “AI will replace jobs.” While there is truth to this statement, the sentiment of the message is starting to shift to a more nuanced perspective.

Instead of “AI will replace jobs,” I’ve been hearing more often the title of a Harvard Business Review article in its stead: “AI Won’t Replace Humans — But Humans With AI Will Replace Humans Without AI.”

The “jobs” response is just one, very practical, reason why we must focus on AI Literacy.

To offer a more humanistic reason as well: it is a right for people to understand the world around them. The world we live in is soaked in AI, and therefore, people deserve to understand that world.

Regardless, AI Literacy will become a crucial competency of a citizen during the fourth industrial revolution. We, as educators, owe it to students (and to ourselves!) to emphasize AI Literacy.

3. What is the AI4K12 AI Framework?

So, are you ready to jump in to AI Literacy?

The organization AI4K12 Identified 5 Big Ideas in AI:

1. Perception: Computers perceive the world using sensors.

2. Representation & Reasoning: AI agents maintain representations of the world and use them for reasoning, using data structures and algorithms.

3. Learning: Computers can learn from data through machine learning, which requires large amounts of training data.

4. Natural Interaction: AI agents need various kinds of knowledge to interact naturally with humans, including language, emotion recognition, and understanding social conventions.

5. Societal Impact: AI can have both positive and negative impacts on society, and it's important to consider ethical design and deployment of AI systems.

I must admit, I don’t think the titles of these 5 Big Ideas do the concepts or content within sufficient justice.

But, you’ll have to be the judge of that!

In each of the following newsletters, I’ll dive into each Big Idea in more depth, and explain how you can introduce these design concepts and ethical quandaries to students of any age.

Class dismissed!

Lewis Poche & Kourtney Bradshaw-Clay